If there has been a prevailing theme in marketing over the past decade, it’s been a constant drive to offer more personalized, better-focused experiences to consumers. With the digital boom that occurred in the past year, these efforts have only accelerated, which has added pressure to brands to scale up their efforts with respect to consumer data.

In this drive for more and better data, however, something has gotten lost: the voice of the consumer. In an effort to build stores of quantitative insights, brands are missing the qualitative side of the story that can prove invaluable to determining consumers’ moods, feelings, impressions, and experiences with a brand, and how that brand fits into the broader tapestry of their lives and the world around them.

By integrating consumer conversations into existing martech stacks, brands are able to drive marketing efforts that leverage their data-focused efforts, but root them in tangible consumer empathy that not only answers the who and where (demographic information), the what and how (which actions a customer has performed), but also the why, the motivating forces that serve as the foundation for robust consumer insights.

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The Existing MarTech Stack Only Tells One Side of the Story

Within the existing marketing paradigm, there has long been a reliance on data-driven tools: Google Analytics, Hubspot, Salesforce; the list goes on. All of these platforms within the martech stack are valuable because they can help identify consumers based on their behavior, create segments from those consumers, and lead to more focused, personalized targeting efforts.

All of this data, collectively, forms the backbone of what we call “big data”. Big data is great; it’s nearly limitless and its scale and quantifiability. Thick data, by contrast, is difficult to scale, but isolates patterns set against the backdrop of social context. In short, big data offers scale without resolution, while thick data efforts provide the clarity needed to understand the why of consumer behavior that underpins big data. One can’t exist without the other.

One of the emerging trends in marketing is divesting from overreliance on big data. As third-party cookies begin to phase out, iOS is cracking down on insights that can be gleaned from emails, and state and federal governments begin passing legislation restricting companies’ collection and use of consumer data, brands are needing to pivot to smaller stores of better, more actionable data. By pairing these quantitative efforts with more robust qualitative tools and focusing on customer conversations, brands are able to see both sides of the insights equation to better offer personalization and tailor experiences to all audiences.

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Integrating Consumer Conversations Into the MarTech Stack

With many quantitative insights tools, the knowledge brands are able to glean are contingent on the existing user lifecycle. Meaning, brands are given information like open rates, clickthrough rates, cart abandonment statistics, time spent on a page, etc.; this information is a valuable “what” metric. It’s important to know what your customers are doing as they interact with your outreach efforts.

Yet beyond that “what” data, answering the why is mostly left to inference. Emails, for example, can be A/B tested and adapted with new messaging, and that success can be measured against previous efforts to determine what works and what doesn’t. This methodology is an inefficient way of finding out what could be accomplished in a short conversation with a customer.

Integrating customer conversations and qualitative insights into the martech stack means finding customers at points of friction, and answering that “why” in the most efficient way possible. “The shortest distance between two points is a straight line,” as the saying goes.

For example, a brand can engage a customer—from the foundation of all the quantitative and demographic information they have—in a real conversation to answer the why. In email, if an existing customer has shown that they aren’t opening any of the promotional emails they receive, they can be invited to have a short conversation with a member of the brand team, and have a discussion about why. Perhaps emails are too frequent, perhaps they’re not interested in the products being featured; there could be any number of reasons why they’re not engaging. By having an honest and open conversation, the brand team can understand the deeper motivations behind consumer behavior and adjust their strategy going forward.

This methodology can be applied to simple site interactions as well. If a user visits the site and leaves, serving them a pop-up for a quick exit interview can be extremely insightful, answering questions such as what brought them to the website, what they didn’t see that they wanted to see, and more. Because this information isn’t tethered to the traditional customer lifecycle, it can be more objective from a consumer perspective, which can be extremely valuable to a brand.

In the past, many of the qualitative insights were gleaned from in-person focus groups. But as video platforms have seen wider adoption in the past two years, consumer conversations can be facilitated at a moment’s notice, with audiences around the world. These tools and workflows exist, and can be easily integrated within a brand’s existing martech stack.

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Qualitative and Quantitative Data Working Together

As quantitative data has a tendency to lack meaning without integrating consumer conversations and qualitative analysis, qualitative analysis needs quantitative data to make connections and provide nuanced insights.

By integrating consumer conversations and qualitative analysis into the martech stack, brands get a full picture of a customer. They can extract raw data to pattern consumer behavior, and dig deeper through conversations to understand the underlying motivations behind those behaviors. In the process, brands are better able to empathize with their customers, which can lead to better personalization to build a lifelong connection and loyalty.